3 papers
cs.MA2026
The Cost of Consensus: Malignant Epistemic Herding and Adaptive Gating in Distributed Multi-Agent Search
David Farr, Iain Cruickshank, Kate Starbird +1
Distributed agents in real-world settings frequently must coordinate under uncertainty with only partial observations. Coordination is necessary to share beliefs to aid in task com…
cs.HC2024
LLM Confidence Evaluation Measures in Zero-Shot CSS Classification
David Farr, Iain Cruickshank, Nico Manzonelli +3
Assessing classification confidence is critical for leveraging large language models (LLMs) in automated labeling tasks, especially in the sensitive domains presented by Computatio…
cs.LG2024
LLM Chain Ensembles for Scalable and Accurate Data Annotation
David Farr, Nico Manzonelli, Iain Cruickshank +2
The ability of large language models (LLMs) to perform zero-shot classification makes them viable solutions for data annotation in rapidly evolving domains where quality labeled da…